########
# Usage: Rscript detail_pathway_boxplot2.R 'P00001' "Healthy,Benign,BRCA,HCC,SCLC"

# 传入参数： target = 'P00001'  
#            cohort.selected = c('Healthy', 'Benign', 'BRCA', 'HCC', 'SCLC')

# 默认传入所有的cohorts
#        Rscript detail_pathway_boxplot1.R 'P00001' "Urine,Bile,CSF,Healthy,Benign,BRCA,CHD,CRC,GC,HCC,KIRC,ML,OV,PAAD,SCLC"
########
library(ggplot2)
library(RColorBrewer)

library(optparse)

option_list <- list(
  make_option("--t", default = "", type = "character", help = "target"),
  make_option("--i", default = "", type = "character", help = "target file"),
  make_option("--c", default = "", type = "character", help = "cohort selected"),
  make_option("--o", default = "", type = "character", help = "output png file")
)
opt <- parse_args(OptionParser(option_list = option_list))

Args = commandArgs()
target = opt$t
cohort.selected = opt$c
cohort.selected = as.vector(unlist(strsplit(cohort.selected, ',')))

# target = 'P00101'
# cohort.selected = c('Healthy', 'Benign', 'BRCA', 'HCC', 'SCLC')
# cohort.selected = c("Urine","Bile","CSF","Healthy","Benign","BRCA","CHD","CRC","GC","HCC","KIRC","ML","OV","PAAD","SCLC")
# path = "D:\\exo\\905\\submit 10\\detail_pathway"
# setwd(path)

targetType = 'pathway'
w = 12
h = 6
outfile = opt$o

infile = opt$i
data.target = read.csv(infile, sep = ',', header = FALSE, row.names = NULL, stringsAsFactors = F)
pathwayName = data.target[1,][5]       ### 获取pathway name
data.target = data.target[-1,]
colnames(data.target) = c('sample', 'type', 'cohort', 'sampleSize', 'score')
data.target = data.target[data.target$cohort %in% cohort.selected,]
data.target$label = paste(data.target$cohort, '\n', '(', data.target$sampleSize, ')', sep = '')   ### label
data.target$score = round(as.numeric(data.target$score), 3)

cohortsNumber = length(cohort.selected)
if (cohortsNumber == 15) {               ### 默认选择除（ESCC, GBM, MEL）外的所有cohort， 且固定cohort顺序
  labelOrder = c("Urine\n(16)", "CSF\n(5)", "Bile\n(15)", "Healthy\n(118)", "Benign\n(130)", "BRCA\n(140)", "CHD\n(12)", "CRC\n(35)", "GC\n(9)", "HCC\n(112)", "KIRC\n(15)", "ML\n(28)", "OV\n(30)", "PAAD\n(164)", "SCLC\n(36)")
  data.target$label = factor(data.target$label, levels = labelOrder)
}

cols = c(brewer.pal(9, "Pastel1"), brewer.pal(9, "Set3"))
pdf(outfile, width = w, height = h)
p = ggplot(data.target, aes(x = label, y = score, fill = label)) +
  geom_boxplot(linetype = "dashed", width = 0.6, outlier.shape = NA, color = "#525252", size = 0.5, notch = TRUE) +
  stat_boxplot(aes(ymin = ..lower.., ymax = ..upper..), width = 0.6, outlier.shape = NA, color = "#525252", size = 0.5, notch = TRUE) +
  stat_boxplot(geom = "errorbar", aes(ymin = ..ymax..), color = "#525252", size = 0.5, width = 0.3) +
  stat_boxplot(geom = "errorbar", aes(ymax = ..ymin..), color = "#525252", size = 0.5, width = 0.3) +
  scale_fill_manual(values = cols) +
  xlab('') +
  ylab("ssGSEA score") +
  ggtitle(pathwayName) +
  theme_bw() +
  theme(panel.grid = element_blank()) +
  theme(axis.title = element_text(size = 12, face = "bold")) +
  theme(plot.title = element_text(size = 14, face = "bold", hjust = 0.5)) +
  guides(fill = FALSE, colour = FALSE) +
  theme(panel.border = element_rect(linetype = 'solid', size = 1.2, fill = NA),
        axis.text.y = element_text(face = 'bold', color = 'black', size = 10, angle = 360),
        axis.text.x = element_text(face = 'bold', color = 'black', size = 10, angle = 360, hjust = 0.5),
        axis.title = element_text(size = 14, face = "bold"))
print(p)
dev.off()
